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generalised linear model (glm) function  (RStudio)

 
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    RStudio generalised linear model (glm) function
    Generalised Linear Model (Glm) Function, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/generalised+linear+models+(glm)/general+linear+model/pm40362756-62-32-36
    Average 90 stars, based on 1 article reviews
    generalised linear model (glm) function - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: The buzz around spatial resolving power and contrast sensitivity in the honeybee, Apis mellifera.
    Article Snippet: To compare spatial resolving power and contrast sensitivity for hymenopterans in relation to the total number of facets and facet diameter we conducted a Generalised Linear Model (GLM) analysis in R (Version 1.1.143, RStudio, Inc. Boston, MA, US).

    Article Title: Inconsistent bioreceptivity of three mortar mixes in subtidal sites
    Article Snippet: To test for statistically significant differences in abundance, species richness, and biomass between the mortar formulas over time within each site, generalised linear models (GLM) were run in R Studio (Version 1.2.1335) with mortar (OPC, GGBS and VP) and interval (3-, 6-, and 12- months) as fixed factors.

    Article Title: Density-dependence inside a marine protected area increases natural mortality and stunts the growth of a spiny lobster
    Article Snippet: Sustainable fisheries management often requires the modelling of stocks under unfished conditions, when the influence of population densities on animal growth and mortality can be substantial.. This can be especially true for species such as spiny rock lobster, which are very habitat specific.. Using western rock lobster (Panulirus cygnus) tag-recapture data from adjacent and similar fished and unfished areas, the key life history parameters of natural mortality and growth were examined and compared under different population density scenarios.

    Article Title: Current vegetation structure and composition of woody species in community‐derived categories of land degradation in a semiarid rangeland in Kunene region, Namibia
    Article Snippet: Generalised Linear Models (GLM) in R-studio (R Core Team, 2013) were used to determine differences in density, mean height and DBH of life stages among the different degradation categories.



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    Antibody response <t>after</t> <t>SARS-CoV-2</t> vaccination in MTX-m ( n = 72), MTX-1ww ( n = 71) and MTX-2ww ( n = 73) groups separated in previously uninfected (no COVID-19) and previously infected (COVID-19) individuals. Results are represented as increment (Δ) of AU/mL between pre-vaccination and post-vaccination samples (1 month after complete vaccination), after adjusting for confounding variables by means of <t>glm</t> (left). Cuzick test was used to assess statistical significance. * p < 0.05, *** p < 0.001. Percentage of poor (below 25 th percentile response), moderate (25 th to 50 th percentile) and good responders (greater than 50 th percentile) to vaccination across groups (right). Fisher exact test was used to check statistical significance. Box plots represent the interquartile ranges, horizontal lines indicate the medians, and error bars extend to the minimum and maximum observed values.
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    Antibody response <t>after</t> <t>SARS-CoV-2</t> vaccination in MTX-m ( n = 72), MTX-1ww ( n = 71) and MTX-2ww ( n = 73) groups separated in previously uninfected (no COVID-19) and previously infected (COVID-19) individuals. Results are represented as increment (Δ) of AU/mL between pre-vaccination and post-vaccination samples (1 month after complete vaccination), after adjusting for confounding variables by means of <t>glm</t> (left). Cuzick test was used to assess statistical significance. * p < 0.05, *** p < 0.001. Percentage of poor (below 25 th percentile response), moderate (25 th to 50 th percentile) and good responders (greater than 50 th percentile) to vaccination across groups (right). Fisher exact test was used to check statistical significance. Box plots represent the interquartile ranges, horizontal lines indicate the medians, and error bars extend to the minimum and maximum observed values.
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    Antibody response after SARS-CoV-2 vaccination in MTX-m ( n = 72), MTX-1ww ( n = 71) and MTX-2ww ( n = 73) groups separated in previously uninfected (no COVID-19) and previously infected (COVID-19) individuals. Results are represented as increment (Δ) of AU/mL between pre-vaccination and post-vaccination samples (1 month after complete vaccination), after adjusting for confounding variables by means of glm (left). Cuzick test was used to assess statistical significance. * p < 0.05, *** p < 0.001. Percentage of poor (below 25 th percentile response), moderate (25 th to 50 th percentile) and good responders (greater than 50 th percentile) to vaccination across groups (right). Fisher exact test was used to check statistical significance. Box plots represent the interquartile ranges, horizontal lines indicate the medians, and error bars extend to the minimum and maximum observed values.

    Journal: NPJ Vaccines

    Article Title: Beneficial effect of temporary methotrexate interruption on B and T cell responses upon SARS-CoV-2 vaccination in patients with rheumatoid arthritis or psoriatic arthritis

    doi: 10.1038/s41541-024-00805-3

    Figure Lengend Snippet: Antibody response after SARS-CoV-2 vaccination in MTX-m ( n = 72), MTX-1ww ( n = 71) and MTX-2ww ( n = 73) groups separated in previously uninfected (no COVID-19) and previously infected (COVID-19) individuals. Results are represented as increment (Δ) of AU/mL between pre-vaccination and post-vaccination samples (1 month after complete vaccination), after adjusting for confounding variables by means of glm (left). Cuzick test was used to assess statistical significance. * p < 0.05, *** p < 0.001. Percentage of poor (below 25 th percentile response), moderate (25 th to 50 th percentile) and good responders (greater than 50 th percentile) to vaccination across groups (right). Fisher exact test was used to check statistical significance. Box plots represent the interquartile ranges, horizontal lines indicate the medians, and error bars extend to the minimum and maximum observed values.

    Article Snippet: To determine which variables could explain variability in humoral and cellular response to SARS-CoV-2 vaccination, we performed a multivariable linear regression model using generalised linear models (GLM) for each dependent variable by using the Stata glm command.

    Techniques: Infection